package torch
 sectionYPositions = computeSectionYPositions($el), 10)"
  x-init="setTimeout(() => sectionYPositions = computeSectionYPositions($el), 10)"
  >
  
  
  PyTorch bindings for OCaml
Install
    
    dune-project
 Dependency
Authors
Maintainers
Sources
  
    
      0.4.tar.gz
    
    
        
    
  
  
  
    
  
  
    
  
        md5=9547e9e025dacd52e405ff699539c582
    
    
  sha512=23fd9bef6f5f11c55171f2383a2f7ca57330511af6521a4579410e002d8667a91e764aecc2deb1cf8d7bf3b0e988cd3020850fa4a5a1ec713dfb110ec7352892
    
    
  doc/torch.vision/Torch_vision/Image/index.html
Module Torch_vision.ImageSource
Source
val load_image : 
  ?resize:(Base.int * Base.int) ->
  Base.string ->
  Torch.Tensor.t Base.Or_error.tload_image ?resize filename returns a tensor containing the pixels for the image in filename. Supported image formats are JPEG and PNG. The resulting tensor has dimensions NCHW (with N = 1). When resize is set, the image is first resized preserving its original ratio then a center crop is taken.
load_images ?resize dir_name is similar to applying load_image to all the images in dir_name. The resulting tensor has dimensions NCHW where N is the number of images.
Source
val load_dataset : 
  dir:Base.string ->
  classes:Base.string Base.list ->
  with_cache:Base.string Base.option ->
  resize:(Base.int * Base.int) ->
  Torch.Dataset_helper.t sectionYPositions = computeSectionYPositions($el), 10)"
  x-init="setTimeout(() => sectionYPositions = computeSectionYPositions($el), 10)"
  >